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Internet of Things (IoT) is a potential technology to be used for data collection tasks in real-world environments. However, due to the difficulty of deploying and testing a real IoT implementation, many researchers end up having to use software simulation to evaluate their proposed techniques. This paper focuses on the use of IoTbased WSN for collecting flood-related data, which would then use by flood-related applications such as flood prediction applications and flood early warning systems. This paper proposed a methodology for simulating the IoT system used for flood data collection. The proposed methodology consists of four main steps which are identifying the flood environment, defining the architecture for flood data collection, simulating the IoT-based WSN flood data collection infrastructure and analyzing the results. The activities for each step are described in detail as to guide other researchers in the same area to adapt the methodology to their research work. [ABSTRACT FROM AUTHOR]

In this paper detailed descriptions of the algorithms used in the pre-processing and feature extraction phases of an offline handwritten character are discussed. In classifying handwritten characters, the stages prior to the classification phase play a role as major as the classification itself. There are many pre-processing functions and methods that can be used and different research works will use different methods. This paper discusses in detail some of the algorithms used in the pre-processing stages of an offline handwritten character image file. This paper serves as part of the whole research work that aims at recognizing handwritten characters. The whole research presents a hybrid approach of HMM and Fuzzy Logic in the field of handwritten character recognition. Fuzzy Logic is used in the classification phase while HMM is used in the process of extracting features for the preparation of linguistic variables of the fuzzy rules. However, only the preprocessing stages as employed by the research are described here. The pre-processing phase starts from reading in the input file, the process of binarization, reference line estimation and thinning of the character image for further use in the next stage of the feature extraction and recognition process. Each of the pre-processing stages and the chain coding process will be described in detail giving improvised algorithms, and examples of the processes on existing samples from the database shown. Where comparing experiments with other methods is done, the experimental results are given. [ABSTRACT FROM AUTHOR]

Information retrieval involves finding some required information in a collection of information or in databases. The information or database need not necessarily be in one language. In other words, language should not limit the finding of information. The way to search for the information is by looking at every item in the collection and when the need to translate the language arises, the techniques and methods developed for the cross-lingual retrieval system is used. This paper reviews some recent researches focusing on topics in cross-lingual information retrieval and their role in current research directions which include new models and paradigms in the wide area of information retrieval. [ABSTRACT FROM AUTHOR]

Shyness is a difficulty experienced by many children in our country. Although it is a norm that Asians exhibit more colourings of shyness (e.g. timidity, passiveness, non-confrontational); studies conducted within the learning domain verifies that this personality trait is being acknowledged as a negative trait, especially among young learners (children) which is likely to affect their potential and performance in the academic platform. Teachers and peers may falsely belief that these students are less capable and less intelligent which may develop a poor perception towards them. However, these shy students find computer-mediated communication to be easier means of interaction than face-toface contact with teachers. In-line with the Malaysian Education Blueprint (2015-2025) by the Malaysian Ministry of Education (MOE), development and use of Information and Communications Technology (ICT) (e.g. e-learning, educational games and other interactive learning platforms through computer interfaces) are very much encouraged. Hence, implementing an interactive artificial tutor (fit with a shyness model) to automatically adapt and interact to the user's emotional state could help in overcoming shyness, at the same time encourage these shy learners to confidently communicate and exhibit their capabilities. This research intends to review the background study on the usefulness of a shyness computational model which will be integrated with an interactive synthetic tutor. The aim of this study is to identify and capture the display features of colourings of shyness (e.g. timidity, passiveness, non-confrontational) through facial features (e.g. smiles, pouting) and vocal behaviours (silences, frequent pauses, filler words and turn-taking patterns) projected by shy young Malaysian learners (children aged between 9-11 years). These markers will be collected and constructed into a shyness model suitable for interactive synthetic agents used in the learning domain for teaching and training young learners in a typical Malaysian academic setting. [ABSTRACT FROM AUTHOR]

Due to information overload, information management for managers in organisations is a big task. It has been recognized that an effective methodology is required to evaluate information to avoid information overload and to retain the critical information for reuse. Various tools and strategies are presented in an attempt to obtain information's "value." This study examines the topic of information overload, the definition of information value, and associated research on the value of information in many fields to resolve this issue. The Bayesian Theorem and information characteristics are used to offer a framework for evaluating information. [ABSTRACT FROM AUTHOR]